There has already been known a machine translation apparatus such that a computer is used to make a morphological analysis of a text in a first language, and transform the text into a target second language in order to bring each text into mutual correspondence of equivalent meaning between different languages (Published Unexamined Patent Application No.03-8082). The term morphological analysis here consists in analyzing an input text to discover its component words and clarifying the syntactic features of each word to be input into the next syntactic analysis phase.
This machine translation apparatus assigns a tentative modification to a component ambiguous in modification of each word isolated through morphological analysis to continue morphological analysis without suspension and translates the components thus assigned the tentative modification in the word order of the text in the final equivalent generation phase.
However, this machine translation apparatus only advances the processing of a component ambiguous in modification to the final processing phase and hence there may arise a case in which it is impossible to decide on an appropriate equivalent to the ambiguous component from among numerous alternative equivalents, in the final equivalent generation phase. Such a case is known as an explosion of ambiguity. Also, there may arise a case such that no optimal equivalent can be selected from among numerous corresponding equivalents even when a translation-is made using the order of a text.
Moreover, where a component in a first language to be translated is ambiguous in equivalent selection, syntactic analysis, and semantic analysis, what is already known is a machine translation apparatus such that ambiguity is removed by using part-of-speech information and syntactic and semantic information about a word sampled from among other components than that component of the text (in the morphological analysis phase), as in No.02-308370.
However, even in such a machine translation apparatus which removes ambiguity by using information extracted from a component other than the component in question in the text, it is necessary to sufficiently distinguish among cases of using each word according to detailed rules obtained through a thorough analysis, including a syntactic analysis and a semantic analysis, inasmuch as it is difficult to bring ambiguous components of a text into correspondence in word level to a translated text. For this reason, cases might sometimes arise where it is impossible to select the optimum equivalent from among alternatives which may be numerous depending on the degree of ambiguity.
There are further proposed methods of removing the ambiguity of word meaning, such as Word Expert (G. Adriaens and S. L. Small, Morgan Kaufmann Publishers, 1988) and Polaroid Word (G. Hirst, Cambridge University Press, 1987), which are still incapable of clearing up ambiguity in selecting equivalents or generating a translated text even when the ambiguity of word meaning can be cleared up. Also, there may arise cases where early determination of word meaning alone results in the compiler's failure to generate the optimum translated text.
There is also a proposed technique for clearing up the ambiguity of word meaning, a transformation-driven translation technique (O. Furuse, E. Sumita, and H. Ida, In Reprint of WGNL, IPSJ, vol. 80-8, November 1990), which presupposes control under which transformational knowledge based on patterns is globally applied and which hence cannot be applied to the local translation processing of texts, unlike the machine translation apparatus of this invention.
Apart from the above-mentioned methods, there is another probabilistic method such that one equivalent is selected from among a plurality of alternative equivalents by a stochastic technique and still another method using paradigms, including idioms as conventionalized turns of phrase. Although any of the above-mentioned methods using rules, probability, and paradigms can be used to obtain a translated text from a source text, it is practically impossible to make a translation with great accuracy by a single method only. Also, even when these methods are applied globally, the application sequence of texts to be applied or the sequence of applied locations might occasionally pose an obstruction to the selection of the optimum solution.